Run List for Data Release Stripe 82 - SN

Stripe 82 Scans

The table below contains a listing of all 305 runs in the Stripe 82 database.
These runs are all on the celestial equator (-1.25 < DEC < 1.25 deg)
below the Galactic plane (b < 0). The RA's covered varies
from starts as early as 295 (-65) degrees ending as late as 60
degrees and beyond. Runs obtained prior to Sep 2005 were obtained as
part of the Legacy survey, under generally photometric conditions.

This SDSS-I Legacy set of Stripe 82 scans includes
runs numbered 94-5052.

SDSS-II Supernovae project runs:

The SDSS-II Supernovae survey repeatedly scanned this stripe in
the Autumn seasons of 2005, 2006 and 2007.

Runs 5566-5924 are from Supernovae season 1.

Runs 6281-6618 are from Supernovae season 2.

Runs 6921-7202 are from Supernovae season 3.

While these Supernovae scans were not generally obtained
in photometric conditions, however an attempt was made
to photometrically calibrate
the objects in the range: -50 < RA < 59 (only,
objects outside this range are generally not well
calibrated), using detections of the same objects in
the photometric scans to set frame-by-frame zeropoint
offsets. You may evaluate if a given run is non-photometric
by looking at the 'seeing' and 'clouds' links associated
with each run (though this information is not available for
all runs).

Low values of seeing and small sky standard deviation
values throughout the run indicate photometric conditions.

QA of non-photometric runs

Additionally, we provide a 'QA' value, which gives the
one sigma fluctuations in the recalibrated g band camcol 3
zero point for fields in this run. The units are
millimags. If this number is zero,
then either no recalibration was done, or the night was photometric.
If this number is non-zero, then, in general, a large number
corresponds to more variable clouds, and in general, less
good photometric calibration can be expected from (at least
part) of these runs.

Coadd runs:

56 Southern strip Legacy and SN season 1 stripe 82 scans had
their pixels coadded and combined into a Southern coadd run
numbered 106. In the
DAS, this run is numbered 100006, rerun 2. Similarly, 64 Northern strip
scans were coadded into run 206 (in the DAS 200006, rerun 2).

If an individual scan is contained in a coadd, then
there appears a coadd run number 106 or 206 in the far right of
the table below.

These coadd runs, reach approximately sqrt(50) ~ 7, or about
2 magnitude fainter in depth.
They have been processed through the PHOTO object detection
pipeline, and their object catalogs are available in the CAS
in the Stripe 82 DB (and in the DAS).

JPEG mosaics of these runs are available in the
Stripe 82 Visual Tools CAS
These mosaics are black and white, and are optimally
stretched to show the deep detection limit of the coadd.

Caveat: The fpC (corrected frames) in the
Camcol 3, run 100006 DAS have a minor problem in that their
header RA, DEC keywords are offset by 0.5 and 1.5 pixels.

Accessing all detections of a given object in Stripe 82

The tables in the Stripe 82 database are large, containing
from 1 to over 100 detections of the same object scanned
at different epochs for over 4 million separate objects.

This can make CASJOBS database queries (the recommended method)
of these multiple detections extremely slow if not properly
structured.

We offer here an example showing techniques on how to speed up your
variable object stripe 82 queries.

We first recommend that you select a set of baseline or
fiducial detections of a set of objects, chosen from just
one North and/or one South scan. The Coadd runs (106,206)
are good for this purpose.
Let's say you're looking for (variable) RR Lyraes with
(g-r)_0 between -0.1 and 0.2 and
g between 16 and 17th magnitude and (to limit the
sample size), 30 < RA < 40 degrees on stripe 82.
Select an initial sample like so from
the stripe82 context in the
Casjobs interface:

Select objid,
ra,dec,
psfmag_g, psfmag_g-extinction_g as g0,
psfmag_u-extinction_u-psfmag_g+extinction_g as umg0,
psfmag_g-extinction_g-psfmag_r+extinction_r as gmr0
into mydb.rr0b
from star
where
run in (106,206) and
ra between 30 and 40 and
psfmag_g-extinction_g-psfmag_r+extinction_r between -0.1 and 0.2
and psfmag_g between 16 and 17

This selects 21 objects , their coordinates and reference magnitudes
and colors into your local MyDB storage area
within CasJobs.
Now let's search the other 303 runs in the Stripe82 DB for
other detections of these same objects (within 2'' or so in
position).
The key is to use the 'htmid' Hierarchical Triangular Mesh ID
field in the photoobjall (star) table to quickly find objects at
or near the same position as the (RA,DEC)s of the 21 stars you
have already picked out in the reference runs (106,206).

select
dbo.fdistancearcmineq(rr0.ra,rr0.dec,q.ra,q.dec)*60 as darcsec,
p.htmid,
q.objid,rr0.objid as rr0objid,
rr0.ra as rr0ra,rr0.dec as qdec into mydb.rrmatches from
mydb.rr0b as rr0,star p,star q where rr0.objid = p.objid
and q.htmid between 2000*(p.htmid/2000) and 2000*(p.htmid/2000+1) and
q.objid != p.objid
and dbo.fdistancearcmineq(rr0.ra,rr0.dec,q.ra,q.dec)*60 < 2 order by
rr0.objid,darcsec

This returns 1704 objects into a table called MyDB.rrmatches,
(about 80 matches for each of the 21 original objects in the list).
Note that it is *extremely* important for efficient queries,
to only reference the ra,dec,objid and htmids of the star database here.
No extraction of psfmag_g, or even run number of anything at this time (see below) in the
big star or galaxy/photoobjall (which may be substituted) database
or else your query will take hours, if it ever finishes. As written,
with a 21 object input list it takes less than 1 minute to finish
(i.e. you can run it in the quick queue).
Now you need to go back and extract the 80 different u,g magnitudes and
colors for the objects you picked out here,
looking for significant fluctuations to get an RR Lyrae.
Try this:

select rr0.ra,rr0.dec,rr0objid,avg(s.psfmag_g) as meang,stdev(s.psfmag_g)
as sigmag,count(*) into mydb.rrmeansb
from star s,mydb.rrmatches m,mydb.rr0b rr0
where s.objid = m.objid and m.rr0objid = rr0.objid
group by rr0.ra,rr0.dec,rr0objid

This returns 21 rows (could be less if any in the original list
was a 'Coadd-only faint detection', you
can figure out which one this is with a left outer join on the mydb.rr0b table).
With the average magnitude and the sigma (dispersion) of all detections,
as well as the ra,dec of the coadd detection and the count
of the number of detections.
Now we need essentially a clipped sigma/mean to see where the
variable objects are,
reject mags more than 1 mag from the mean for each of the 19 objects.

select stdev(s.psfmag_g) as clippedsigma,avg(s.psfmag_g) as
clippedavg,m.rr0objid,count(*)
from mydb.rrmatches m,mydb.rrmeansb r,star s where
m.rr0objid = r.rr0objid and s.objid = m.objid
and s.psfmag_g between r.meang-1 and r.meang+1 group by m.rr0objid

We look for objects with a big sigma, and we have about 5/21, one is:
objid = 8647475120919150728 with a sigma of 0.30 mags.
Let's look at all 85 detections...

Plotting psfmag_g vs. mjd_r shows a an object with about a 1 magnitude
amplitude in g band variability, this indicates some sort of variable object,
perhaps an RR Lyrae, or perhaps a longer period variable.

NOTES

1
Two interleaving imaging runs (or "stripes") are required to fill an area on the
sky. These are designated by "N" and "S".

2
"field start" and "field end" are the first and last fields from the run
which were able to be processed. Note that for some runs there may be gaps
in between these when the data quality drops below the tolerances of the
processing software. It is also important to note that the field is simply
a rolling number for each run and does not denote a unique position
on the sky. For example, field 100 will not in general contain the same region
of the sky for different runs.

3
Estimates of the seeing (median FWHM in arcseconds) as a function of
field number are linked to aid in data quality assessment.